referrals
When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy.
Skill by coreyhaines31
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/coreyhaines31-referrals
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About
Use cases: documents, marketing, marketing-content, payments-billing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/referrals
What's inside
- Skill name
referrals- Description
- When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' 'partner program,' 'referral incentive,' 'how to get referrals,' 'customers referring customers,' 'affiliate payout,' 'get more reviews,' 'G2 reviews,' 'review campaign,' or 'respond to a bad review.' Use this whenever someone wants existing users or partners to bring in new customers. For launch-specific virality, see launch.
- License
- MIT
- Metadata
- version: 2.2.1
- Instructions
- 278 lines in SKILL.md · view on GitHub
Files (9)
- SKILL.md
- evals.json · evals/
- affiliate-operations.md · references/
- affiliate-programs.md · references/
- program-examples.md · references/
- review-platform-rules.md · references/
- review-program-operations.md · references/
- review-programs.md · references/
- viral-mechanisms.md · references/
SKILL.md (first lines)
# Referral & Affiliate Programs You are an expert in viral growth and referral marketing. Your goal is to help design and optimize programs that turn customers into growth engines. ## Before Starting **Check for product marketing context first:** If `.agents/product-marketing.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task. Gather this context (ask if not provided): ### 1. Program Type - Customer referral program, affiliate program, or both? - B2B or B2C? - What's the average customer LTV? - What's your current CAC from other channels? ### 2. Current State - Existing referral/affiliate program? - Current referral rate (% who refer)? - What incentives have you tried? ### 3. Product Fit - Is your product shareable? - Does it have network effects? - Do customers naturally talk about it? ### 4. Resources - Tools/platforms you use or consider? - Budget for referral incentives? --- ## Should You Engineer Virality First? Before building a reward-driven program, check whether virality can be **built into the product** — often cheaper and more durable than paid referrals. But **don't force virality where it doesn't naturally fit.** Place the product on the **Viral Potential Spectrum**: - **Natural** (build for it): collaboration tools, communication tools, user-facing outputs — every use exposes the product to non-users. - **Limited** (don't force it): backend, competitive-advantage, internal-only, and infrastructure products. Invest in referral programs, content, and partnerships instead. If the product is on the natural end, consider **product-embedded viral mechanisms** (Powered By badges, exposure loops, social sharing, embeds, watermarks) before or alongside a reward program. **For the spectrum diagnostic, the 7 viral mechanisms, value-presentation and timing best practices, and affiliate power-law mechanics**: See [references/viral-mechanisms.md](references/viral-mechanisms.md) --- ## Referral vs. Affiliate ### Customer Referral Programs **Best for:** - Existing customers recommending to their network - Products with natural word-of-mouth - Lower-ticket or self-serve products **Characteristics:** - Referrer is an existing customer - One-time or limited rewards - Higher trust, lower volume ### Affiliate Programs For partner recruitment/activation, cohort economics, executable terms, reconciliation, and measured incremental growth, load [the operating playbook](references/affiliate-operations.md). This expands the existing affiliate branch instead of creating an overlapping skill. **Best for:** - Reaching audiences you don't have access to - Content creators, influencers, bloggers - Higher-ticket products that justify commissions **Characteristics:** - Affiliates may not be customers - Ongoing commission relationship - Higher volume, variable trust --- ## Referral Program Design ### The Referral Loop ``` Trigger Moment → Share Action → Convert Referred → Reward → (Loop) ``` ### Step 1: Identify Trigger Moments **High-intent moments:** - Right after first "aha" moment - After achieving a milestone - After exceptional support - After renewing or upgrading ### Step 2: Design Share Mechanism **Ranked by effectiveness:** 1. In-product sharing (highest conversion) 2. Personalized link 3. Email invitation 4. Social sharing 5. Referral code (works offline) ### Step 3: Choose Incentive Structure **Single-sided rewards** (referrer only): Simpler, works for high-value products **Double-sided rewards** (both parties): Higher conversion, win-win framing **Tiered rewards**: Gamifies referral process, increases engagement **Present the reward with the bigger-*feeling* number** — "lead with the larger number" (say "$10 off," not "40% off," on a low-priced product). Reward at the **aha moment or milestone**, not signup. Reduce friction: one-click share, pre-written messages. **For examples and incentive sizing**: See [references/program-examples.md](references/program-examples.md) **For product-embedded virality, value-presentation rules, and affiliate power-law mechanics**: See [references/viral-mechanisms.md](references/viral-mechanisms.md) --- ## Program Optimization
From coreyhaines31/marketingskills, MIT.
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Signals
- Stars
- 56,355
- Forks
- 8,329
- Open issues
- 17
- Last commit (this folder)
- Oct 10, 2026 (17 days ago)
- Last release
- Oct 19, 2026 (7 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 2.2.1
- License
- MIT
- Repository
- github.com/coreyhaines31/marketingskills
- Website
- marketing-skills.com
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
referrals skill. Agent Mart. https://agentmart.dev/skills/coreyhaines31-referrals (last updated 2026-10-24)